On the maximal achievable accuracy in nonlinear filtering problems

The optimal filtering error for a class of nonlinear cone-bounded filtering problems is analyzed for the case of observation noise intensity tending to zero. A sufficient condition for the resulting optimal error covariance matrix to tend to zero is derived by relating the nonlinear filtering problems to linear ones. The results are specialized for the case of nonlinear autoregressive moving-average (ARMA) processes     

Effects of alcohol on psychophysiological hyperreactivity to nonaversive and aversive stimuli in men at high risk for alcoholism.

Psychophysiological reactivity to nonaversive (1-KHz, 70-db tones) and aversive stimuli (shock) was examined in nonalcoholic men with multigenerational family histories (MFH) of alcoholism and family history negative (FH–) men, while sober and after consuming alcohol. In comparison with FH– Ss, sober MFH Ss had significantly larger skin conductance (SC) orienting responses (ORs), shorter OR latencies, slower habituation rates to the tones, and larger increases in heart rate and vasoconstriction to the shock. Alcohol dampened the magnitude of the SC-OR to the tones and the degree of cardiovascular reactivity to the shocks and increased the habituation rate to the tones in MFH Ss only. Alcohol consumption also increased the SC-OR recovery time in FH– Ss only. The MFH Ss' pattern of psychophysiological hyperreactivity is discussed in terms of a potential dysfunction in stimulus–response regulation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

On the parameters estimation of continuous-time ARMA processes from noisy observations

Recently, an iterative algorithm has been presented for estimating the parameters of partially observed continuous-time processes [1]. In this note we concentrate on continuous-time ARMA processes observed in white noise. A maximum a-posteriori (MAP) estimator is defined for the trajectory of the parameters' random process. This approach enables the MAP estimation of randomly slowly varying parameters, and extends the conventional treatment of time-invariant parameters. The iterative algorithm derived for the MAP estimation, increases the posterior probability of the parameters in each iteration, and converges to a stationary point of the posterior probability functional. Each iteration involves a standard linear smoother followed by a finite-dimensional linear system, and thus is easily implemented.     

When is the generalized likelihood ratio test optimal?

The generalized likelihood ratio test (GLRT), which is commonly used in composite hypothesis testing problems, is investigated. Conditions for asymptotic optimality of the GLRT in the Neyman-Pearson sense are studied and discussed. First, a general necessary and sufficient condition is established, and then based on this, a sufficient condition, which is easier to verify, is derived. A counterexample where the GLRT is not optimal, is provided as well. A conjecture is stated concerning the optimality of the GLRT for the class of finite-state sources     

Cogan''s syndrome: a review of otologic management and 10-year follow-up of a pediatric case

Benign hereditary chorea is an uncommon inherited form of childhood chorea that can be mistaken for much more serious disorders, such as Huntington disease. The clinical manifestations of this condition are reviewed, emphasizing the differential diagnosis, treatment modalities, and evaluation of childhood chorea.     

Linear multiuser receivers in random environments

We study the signal-to-interference (SIR) performance of linear multiuser receivers in random environments, where signals from the users arrive in “random directions.” Such a random environment may arise in a DS-CDMA system with random signature sequences, or in a system with antenna diversity where the randomness is due to channel fading. Assuming that such random directions can be tracked by the receiver, the resulting SIR performance is a function of the directions and therefore also random. We study the asymptotic distribution of this random performance in the regime where both the number of users K and the number of degrees of freedom N in the system are large, but keeping their ratio fixed. Our results show that for both the decorrelator and the minimum mean-square error (MMSE) receiver, the variance of the SIR distribution decreases like 1/N, and the SIR distribution is asymptotically Gaussian. We compute closed-form expressions for the asymptotic means and variances for both receivers. Simulation results are presented to verify the accuracy of the asymptotic results for finite-sized systems     

Approximate and limit results for nonlinear filters with smallobservation noise: the linear sensor and constant diffusion coefficientcase

Recursive approximations for a class of filtering problems are presented. This class is characterized by linear observation sensor, constant diffusion terms, and, for the multidimensional problem, potential-like conditions on the drift. For the case of small observation noise, these approximations are used to demonstrate the Gaussian limiting structure of the optimal nonlinear filter     

A large deviations analysis of range tracking loops

Large deviations theory is applied to the analysis of a discrete time range tracking loop. It is shown that the resulting asymptotics differ from those of the continuous time diffusion limit     

PAC learning with generalized samples and an applicaiton tostochastic geometry

An extension of the standard probably approximately correct (PAC) learning model that allows the use of generalized samples is introduced. A generalized sample is viewed as a pair consisting of a functional on the concept class together with the value obtained by the functional operating on the unknown concept. It appears that this model can be applied to a number of problems in signal processing and geometric reconstruction to provide sample size bounds under a PAC criterion. A specific application of the generalized model to a problem of curve reconstruction is considered, and some connections with a result from stochastic geometry are discussed